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Hubert Plisiecki

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#machine learning Preprint Sep 2026

Cheap and Powerful Tests for Supervised Subspaces: Per-Component Inference for PLS

Partial Least Squares (PLS) regression extracts a few outcome-aligned directions in a high-dimensional X and is widely used across applied science, but inference on the resulting fit is either expensive, biased and discouraged, or absent. We reduce inference to held-out OLS refits of the supervised subspace, a primitiv...

Paweł Lenartowicz, Hubert Plisiecki · 0 citations
Jul 2026

The Two-Process Theory of Machine Self-Report

The first language-model-specific psychometric theory: a two-process theory of machine self-report of language models that reflects the structure imposed on self-report by a training regime and may differ under others is proposed.

Hubert Plisiecki, Filip Chmielewski, Kacper Dudzic et al. · 1 citation
Preprint Aug 2026

How LLMs Respond to Escalating Delusions: Four Longitudinal Trajectories of Model Behavior

The widespread use of LLMs among psychiatric populations has raised concerns regarding their safety and potential iatrogenic impact in the context of AI psychosis. While growing literature conceptualizes AI psychosis and documents case studies, empirical evidence tracing AI-exacerbated psychotic processes remains scarc...

Anna Sterna, Kacper Dudzic, K. Drożdż et al. · 0 citations

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